Lepton Search: Build a Conversational AI Search Engine in 500 Lines of Code 63

Lepton Search, an open-source conversational ai search engine, is launched by Lepton AI, founded by former Alibaba Vice President of Technology Yangqing Jia. The core code of Lepton Search is written in only about 500 lines of Python and supports integration with large language models (LLMs) and search engines.

Main Features of Lepton Search

• Built-in large language model support: By integrating large language models such as Mixtral-8x7b, Lepton Search is able to deliver high-quality text understanding and generation capabilities, and therefore can provide more accurate and in-depth answers.

• Built-in search engine support: Combined with the capabilities of search engines to quickly retrieve information from the web, with two default supported search engines: Bing and Google.

• Customizable user interface: A customizable and beautiful UI.

• Shareable cached search results: Users can easily share search results, save them, and preserve them through the caching feature, reducing the need for repeated searches.

• Multilingual support: Supports multiple languages including Chinese, English, French, German, and Japanese.

Technology and Implementation

• The technology behind Lepton Search includes using the Mixtral-8x7b large model hosted on its own cloud, as well as calling the Bing search engine API for data retrieval.

• In terms of data storage, Lepton Search relies on Lepton KV, the serverless storage offering from Lepton AI.

• The front-end and back-end design of Lepton Search makes it easy for developers to deploy and customize.

Open Source and Deployment

• Yangqing Jia announced on Twitter that Lepton Search is open-sourced under the Apache License, making it free for individuals and enterprises to use.

• There are two deployment methods: local deployment and deployment based on the Lepton cloud. Local deployment is simple and quick, accomplished through a few commands, including cloning the project, installing the Lepton AI library, setting up the Bing API key, building the front-end, and running the server.

• For a quick try, users can deploy directly by clicking the "Deploy" button on the GitHub page, and then configure the search engine API key.

How to Use Lepton Search

1. Download the Lepton Search source code from GitHub and follow the official documentation for installation and configuration.

2. Lepton Search's search engine uses Bing's search API. Users need to obtain a Bing API key, set the Bing key, and build the front-end network.

3. After configuration is complete, start Lepton Search's backend server and begin using the conversational search feature.

Lepton Search project address: https://github.com/leptonai/search_with_lepton